from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.198 | 0.0 | -1 | 1 | 0.049 | 0.000 | 0.229 | 0.229 | See | See |
| 3 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.108 | 0.0 | -1 | 5 | 0.046 | 0.001 | 0.230 | 0.230 | See | See |
| 6 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.012 | 0.001 | 6.503 | 0.0 | 1 | 100 | 0.046 | 0.000 | 0.268 | 0.268 | See | See |
| 9 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.193 | 0.0 | -1 | 100 | 0.047 | 0.000 | 0.236 | 0.236 | See | See |
| 12 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.189 | 0.0 | 1 | 5 | 0.047 | 0.000 | 0.242 | 0.242 | See | See |
| 15 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.167 | 0.0 | 1 | 1 | 0.049 | 0.000 | 0.239 | 0.239 | See | See |
| 18 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.364 | 0.0 | -1 | 1 | 0.008 | 0.000 | 0.534 | 0.534 | See | See |
| 21 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.358 | 0.0 | -1 | 5 | 0.008 | 0.000 | 0.541 | 0.541 | See | See |
| 24 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.374 | 0.0 | 1 | 100 | 0.009 | 0.000 | 0.513 | 0.513 | See | See |
| 27 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.375 | 0.0 | -1 | 100 | 0.009 | 0.001 | 0.484 | 0.486 | See | See |
| 30 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.373 | 0.0 | 1 | 5 | 0.009 | 0.000 | 0.493 | 0.493 | See | See |
| 33 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.373 | 0.0 | 1 | 1 | 0.008 | 0.000 | 0.490 | 0.490 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 1.959 | 0.055 | 0.000 | 0.002 | -1 | 1 | 0.181 | 0.005 | 11.059 | 11.059 | See | See |
| 2 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.023 | 0.004 | 0.000 | 0.023 | -1 | 1 | 0.009 | 0.000 | 2.474 | 2.474 | See | See |
| 4 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 3.111 | 0.088 | 0.000 | 0.003 | -1 | 5 | 0.177 | 0.000 | 17.199 | 17.205 | See | See |
| 5 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.026 | 0.003 | 0.000 | 0.026 | -1 | 5 | 0.009 | 0.000 | 3.055 | 3.057 | See | See |
| 7 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 2.100 | 0.004 | 0.000 | 0.002 | 1 | 100 | 0.211 | 0.001 | 11.857 | 11.857 | See | See |
| 8 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.023 | 0.005 | 0.000 | 0.023 | 1 | 100 | 0.009 | 0.000 | 2.593 | 2.594 | See | See |
| 10 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 2.887 | 0.043 | 0.000 | 0.003 | -1 | 100 | 0.212 | 0.001 | 13.634 | 13.634 | See | See |
| 11 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.025 | 0.002 | 0.000 | 0.025 | -1 | 100 | 0.009 | 0.000 | 2.824 | 2.825 | See | See |
| 13 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 2.086 | 0.002 | 0.000 | 0.002 | 1 | 5 | 0.177 | 0.000 | 9.869 | 9.869 | See | See |
| 14 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.020 | 0.000 | 0.000 | 0.020 | 1 | 5 | 0.009 | 0.000 | 2.280 | 2.281 | See | See |
| 16 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 1.183 | 0.005 | 0.001 | 0.001 | 1 | 1 | 0.177 | 0.000 | 6.681 | 6.681 | See | See |
| 17 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 1 | 0.009 | 0.000 | 2.182 | 2.183 | See | See |
| 19 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 1.827 | 0.015 | 0.000 | 0.002 | -1 | 1 | 0.026 | 0.000 | 70.460 | 70.488 | See | See |
| 20 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.008 | 0.003 | 0.000 | 0.008 | -1 | 1 | 0.001 | 0.000 | 11.031 | 11.174 | See | See |
| 22 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.814 | 0.024 | 0.000 | 0.003 | -1 | 5 | 0.027 | 0.001 | 109.050 | 109.056 | See | See |
| 23 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.009 | 0.001 | 0.000 | 0.009 | -1 | 5 | 0.001 | 0.000 | 12.067 | 12.265 | See | See |
| 25 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.071 | 0.004 | 0.000 | 0.002 | 1 | 100 | 0.061 | 0.000 | 76.099 | 76.164 | See | See |
| 26 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 3.034 | 3.226 | See | See |
| 28 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.827 | 0.016 | 0.000 | 0.003 | -1 | 100 | 0.063 | 0.004 | 45.037 | 45.108 | See | See |
| 29 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.008 | 0.002 | 0.000 | 0.008 | -1 | 100 | 0.001 | 0.000 | 10.241 | 10.403 | See | See |
| 31 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.055 | 0.004 | 0.000 | 0.002 | 1 | 5 | 0.027 | 0.000 | 33.908 | 33.909 | See | See |
| 32 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 3.520 | 3.566 | See | See |
| 34 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 1.086 | 0.002 | 0.000 | 0.001 | 1 | 1 | 0.026 | 0.001 | 40.318 | 40.319 | See | See |
| 35 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.612 | 2.667 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.196 | 0.138 | 0.025 | 0.0 | 1 | 5 | 0.721 | 0.005 | 4.220 | 4.221 | See | See |
| 3 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.635 | 0.039 | 0.022 | 0.0 | -1 | 5 | 0.715 | 0.016 | 4.913 | 4.914 | See | See |
| 6 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.569 | 0.019 | 0.022 | 0.0 | -1 | 1 | 0.757 | 0.019 | 4.933 | 4.934 | See | See |
| 9 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.682 | 0.034 | 0.022 | 0.0 | 1 | 1 | 0.724 | 0.013 | 5.147 | 5.148 | See | See |
| 12 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.648 | 0.035 | 0.022 | 0.0 | 1 | 100 | 0.740 | 0.015 | 5.058 | 5.058 | See | See |
| 15 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.829 | 0.046 | 0.021 | 0.0 | -1 | 100 | 0.728 | 0.014 | 5.258 | 5.259 | See | See |
| 18 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.158 | 0.166 | See | See |
| 21 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | -1 | 5 | 0.001 | 0.000 | 0.394 | 0.473 | See | See |
| 24 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | -1 | 1 | 0.003 | 0.001 | 0.614 | 0.622 | See | See |
| 27 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.562 | 0.570 | See | See |
| 30 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | 1 | 100 | 0.001 | 0.001 | 0.612 | 0.619 | See | See |
| 33 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.616 | 0.623 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 1.597 | 0.014 | 0.000 | 0.002 | 1 | 5 | 0.207 | 0.006 | 13.482 | 13.484 | See | See |
| 2 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 5.961 | 6.631 | See | See |
| 4 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 0.924 | 0.009 | 0.000 | 0.001 | -1 | 5 | 0.197 | 0.001 | 1.561 | 1.561 | See | See |
| 5 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 0.000 | 0.000 | 5.215 | 5.704 | See | See |
| 7 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 0.499 | 0.008 | 0.000 | 0.000 | -1 | 1 | 0.118 | 0.002 | 4.202 | 4.207 | See | See |
| 8 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 11.199 | 12.468 | See | See |
| 10 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 0.833 | 0.005 | 0.000 | 0.001 | 1 | 1 | 0.119 | 0.005 | 4.239 | 4.239 | See | See |
| 11 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 4.202 | 4.722 | See | See |
| 13 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 5.643 | 0.082 | 0.000 | 0.006 | 1 | 100 | 0.592 | 0.008 | 27.285 | 27.297 | See | See |
| 14 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 9.963 | 10.848 | See | See |
| 16 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 3.094 | 0.054 | 0.000 | 0.003 | -1 | 100 | 0.605 | 0.011 | 5.109 | 5.110 | See | See |
| 17 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 0.001 | 0.000 | 8.303 | 9.065 | See | See |
| 19 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.019 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 39.989 | 41.368 | See | See |
| 20 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 5.052 | 6.491 | See | See |
| 22 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.022 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.001 | 0.000 | 4.660 | 4.672 | See | See |
| 23 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 16.596 | 21.262 | See | See |
| 25 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.021 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.000 | 0.000 | 42.266 | 43.569 | See | See |
| 26 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.000 | 0.000 | 17.162 | 21.557 | See | See |
| 28 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.018 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.000 | 0.000 | 25.215 | 25.686 | See | See |
| 29 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 5.442 | 7.189 | See | See |
| 31 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.033 | 0.000 | 0.000 | 0.000 | 1 | 100 | 0.005 | 0.000 | 43.573 | 44.253 | See | See |
| 32 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 5.371 | 7.032 | See | See |
| 34 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.033 | 0.000 | 0.000 | 0.000 | -1 | 100 | 0.005 | 0.000 | 7.296 | 7.308 | See | See |
| 35 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 16.767 | 21.248 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 2 | 0.558 | 0.004 | 30 | 0.029 | 0.0 | k-means++ | 0.401 | 0.019 | 1.391 | 1.392 | See | See |
| 3 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 2 | 0.485 | 0.003 | 30 | 0.033 | 0.0 | random | 0.369 | 0.013 | 1.315 | 1.316 | See | See |
| 6 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 100 | 5.832 | 0.045 | 30 | 0.137 | 0.0 | k-means++ | 2.987 | 0.143 | 1.952 | 1.955 | See | See |
| 9 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 100 | 5.555 | 0.039 | 30 | 0.144 | 0.0 | random | 2.893 | 0.019 | 1.920 | 1.920 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.010 | 0.000 | k-means++ | 0.0 | 0.0 | 10.636 | 13.094 | See | See |
| 2 | KMeans_tall | sklearn | predict | 1000000 | 1 | 2 | 0.001 | 0.0 | 30 | 0.000 | 0.001 | k-means++ | 0.0 | 0.0 | 10.270 | 13.511 | See | See |
| 4 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 2 | 0.001 | 0.0 | 30 | 0.012 | 0.000 | random | 0.0 | 0.0 | 8.489 | 10.159 | See | See |
| 5 | KMeans_tall | sklearn | predict | 1000000 | 1 | 2 | 0.001 | 0.0 | 30 | 0.000 | 0.001 | random | 0.0 | 0.0 | 10.842 | 13.755 | See | See |
| 7 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.481 | 0.000 | k-means++ | 0.0 | 0.0 | 5.403 | 5.992 | See | See |
| 8 | KMeans_tall | sklearn | predict | 1000000 | 1 | 100 | 0.001 | 0.0 | 30 | 0.001 | 0.001 | k-means++ | 0.0 | 0.0 | 10.529 | 13.211 | See | See |
| 10 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.494 | 0.000 | random | 0.0 | 0.0 | 5.837 | 6.531 | See | See |
| 11 | KMeans_tall | sklearn | predict | 1000000 | 1 | 100 | 0.001 | 0.0 | 30 | 0.001 | 0.001 | random | 0.0 | 0.0 | 10.418 | 13.319 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | library | diff_adjusted_rand_scores | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KMeans_short | sklearn | 0.001361 | predict | 10000 | 1000 | 2 | 0.001857 | 0.000171 | 20 | 0.008616 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.000744 | 0.000494 | 0.000095 | -0.000617 | 3.762837 | 3.832135 |
| 7 | KMeans_short | sklearn | 0.002111 | predict | 10000 | 1000 | 100 | 0.002516 | 0.000255 | 20 | 0.317912 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.340206 | 0.001026 | 0.000151 | 0.342317 | 2.452647 | 2.479219 |
| 10 | KMeans_short | sklearn | 0.016992 | predict | 10000 | 1000 | 100 | 0.002428 | 0.000273 | 20 | 0.329554 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.321348 | 0.001018 | 0.000147 | 0.338339 | 2.383608 | 2.408166 |
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | sklearn | fit | 10000 | 10000 | 2 | 0.077 | 0.001 | 20 | 0.002 | 0.0 | random | 0.026 | 0.001 | 3.016 | 3.017 | See | See |
| 3 | KMeans_short | sklearn | fit | 10000 | 10000 | 2 | 0.217 | 0.002 | 20 | 0.001 | 0.0 | k-means++ | 0.080 | 0.001 | 2.698 | 2.698 | See | See |
| 6 | KMeans_short | sklearn | fit | 10000 | 10000 | 100 | 0.199 | 0.003 | 20 | 0.040 | 0.0 | random | 0.105 | 0.001 | 1.906 | 1.906 | See | See |
| 9 | KMeans_short | sklearn | fit | 10000 | 10000 | 100 | 0.563 | 0.016 | 20 | 0.014 | 0.0 | k-means++ | 0.299 | 0.001 | 1.885 | 1.885 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | sklearn | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | random | 0.001 | 0.0 | 3.698 | 3.774 | See | See |
| 2 | KMeans_short | sklearn | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | random | 0.000 | 0.0 | 10.520 | 12.830 | See | See |
| 4 | KMeans_short | sklearn | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | k-means++ | 0.000 | 0.0 | 3.763 | 3.832 | See | See |
| 5 | KMeans_short | sklearn | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | k-means++ | 0.000 | 0.0 | 10.133 | 12.328 | See | See |
| 7 | KMeans_short | sklearn | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.318 | 0.000 | random | 0.001 | 0.0 | 2.453 | 2.479 | See | See |
| 8 | KMeans_short | sklearn | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | random | 0.000 | 0.0 | 8.424 | 9.800 | See | See |
| 10 | KMeans_short | sklearn | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.330 | 0.000 | k-means++ | 0.001 | 0.0 | 2.384 | 2.408 | See | See |
| 11 | KMeans_short | sklearn | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | k-means++ | 0.000 | 0.0 | 8.552 | 9.972 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | sklearn | fit | 1000000 | 1000000 | 100 | 11.222 | 0.155 | [20] | 0.071 | 0.000 | 2.036 | 0.076 | 5.512 | 5.516 | See | See |
| 3 | LogisticRegression | sklearn | fit | 1000 | 1000 | 10000 | 0.808 | 0.009 | [27] | 0.099 | 0.001 | 0.976 | 0.034 | 0.828 | 0.828 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | sklearn | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 2.471 | 0.0 | 0.000 | 0.0 | 0.940 | 1.027 | See | See |
| 2 | LogisticRegression | sklearn | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.012 | 0.0 | 0.000 | 0.0 | 0.388 | 0.451 | See | See |
| 4 | LogisticRegression | sklearn | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [27] | 4.994 | 0.0 | 0.004 | 0.0 | 0.442 | 0.444 | See | See |
| 5 | LogisticRegression | sklearn | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [27] | 0.821 | 0.0 | 0.001 | 0.0 | 0.137 | 0.143 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | sklearn | fit | 1000 | 1000 | 10000 | 0.171 | 0.010 | 0.467 | 0.0 | 0.180 | 0.001 | 0.950 | 0.950 | See | See |
| 3 | Ridge | sklearn | fit | 1000000 | 1000000 | 100 | 1.090 | 0.048 | 0.734 | 0.0 | 0.225 | 0.007 | 4.842 | 4.844 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | sklearn | predict | 1000 | 1000 | 10000 | 0.012 | 0.001 | 6.452 | 0.0 | 0.019 | 0.0 | 0.662 | 0.662 | See | See |
| 2 | Ridge | sklearn | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | 1.102 | 0.0 | 0.000 | 0.0 | 0.669 | 0.800 | See | See |
| 4 | Ridge | sklearn | predict | 1000000 | 1000 | 100 | 0.000 | 0.000 | 5.311 | 0.0 | 0.000 | 0.0 | 0.658 | 0.756 | See | See |
| 5 | Ridge | sklearn | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | 0.014 | 0.0 | 0.000 | 0.0 | 0.626 | 0.771 | See | See |